Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method for providing big data analytics, the method comprising steps of: providing a web-based explorer interface module to receive a database schema of a source database, wherein the database schema indicates how entities that make up a database relate to one another; configuring a pre-defined or custom based adapter module, which programmatically refers to the database schema defined using the web-based explorer interface module, to retrieve data from the source database of said database schema and ingest the retrieved data into a target database; providing a processor manager module configured to process the ingested data to obtain metrics, wherein the processing is based on how the metrics are defined; providing a predict manager module configured to assign an analytic task to a data scientist, wherein the data scientist uses a curl tool to pull said ingested data via REST (Representational State Transfer) architectural style APIs, and once the ingested data is built, the data scientist deploys a scoring engine using the curl tool; and providing a user interface module configured to provide visualization of the ingested data, in the form of charts; wherein the modules are coupled with a framework and integrated for ad-hoc big data gathering.
This invention relates to a system for big data analytics, addressing the challenge of efficiently collecting, processing, and visualizing large datasets from diverse sources. The system includes a web-based explorer interface that allows users to input a database schema, which defines the relationships between entities in a source database. An adapter module, either pre-defined or customizable, uses this schema to programmatically retrieve data from the source database and ingest it into a target database. A processor manager module processes the ingested data to generate metrics based on predefined definitions. A predict manager module assigns analytic tasks to data scientists, who use a curl tool to access the ingested data via REST APIs. Once the data is processed, the data scientist deploys a scoring engine using the same curl tool. A user interface module provides visualizations of the ingested data in the form of charts. All modules are integrated into a framework that supports ad-hoc big data gathering, enabling flexible and scalable analytics operations. The system streamlines data extraction, processing, and visualization, making it easier for organizations to derive insights from large datasets.
2. The method of claim 1 , wherein the database schema is stored in form of structured and unstructured big data.
A system and method for managing database schemas involves storing the schema in a hybrid format combining structured and unstructured big data. The approach addresses challenges in handling large-scale, diverse data types by integrating structured schema definitions with unstructured data elements, enabling flexible and scalable schema management. The structured portion organizes metadata, relationships, and constraints, while the unstructured portion accommodates raw, semi-structured, or evolving data formats. This hybrid storage allows for efficient querying, indexing, and adaptation to dynamic data environments. The method supports schema evolution by dynamically updating both structured and unstructured components, ensuring compatibility with diverse data sources and applications. The system may include a processing module to parse, validate, and transform schema data, along with an interface for user interaction and schema modification. The hybrid storage approach improves performance, scalability, and adaptability in big data environments where traditional schema management systems struggle with complexity and volume.
3. The method of claim 1 , wherein each of the modules is created, tested initiated, stopped, restarted upgraded, modified, deleted, deployed, and un-deployed based on the request from application developers or software engineers or data scientists or business user.
This invention relates to a modular software system designed to enable dynamic management of software modules by various users, including application developers, software engineers, data scientists, and business users. The system allows these users to perform a wide range of operations on individual modules, such as creation, testing, initiation, stopping, restarting, upgrading, modification, deletion, deployment, and undeployment. Each module operates independently, enabling flexible and scalable software development and maintenance. The system ensures that users with appropriate permissions can control the lifecycle of modules without requiring centralized intervention, improving efficiency and adaptability in software development workflows. The modular architecture supports rapid iteration, testing, and deployment, making it suitable for agile development environments. The invention addresses the need for a decentralized, user-driven approach to module management, reducing bottlenecks and enhancing collaboration across different roles in software development and data science.
4. The method of claim 1 , wherein the framework is equipped with monitoring, management and control of service setup, software and hardware setup implemented by means of web-based portals in the framework.
This invention relates to a framework for monitoring, managing, and controlling service, software, and hardware setups using web-based portals. The framework provides centralized oversight of system configurations, ensuring efficient deployment and maintenance of services, applications, and hardware components. The web-based portals enable remote access, allowing administrators to monitor system performance, configure settings, and troubleshoot issues without physical intervention. The framework integrates monitoring tools to track system health, usage metrics, and potential failures, while management features facilitate software updates, hardware configurations, and service deployments. Control mechanisms allow for real-time adjustments, such as scaling resources or modifying service parameters, to optimize performance. The system supports automation, reducing manual intervention and improving operational efficiency. By leveraging web-based interfaces, the framework ensures accessibility across different devices and locations, enhancing flexibility and responsiveness in managing complex IT environments. The invention addresses the need for streamlined, centralized control of diverse system components, improving reliability and reducing downtime.
5. The method of claim 1 , wherein the framework is configured to enable identity management, policy driven access control, data privacy controls and authentication of various levels accessing the framework.
This invention relates to a framework for managing digital identities, access control, data privacy, and authentication in a computing environment. The framework provides a centralized system to handle identity management, ensuring secure and efficient user authentication across multiple applications and services. It enforces policy-driven access control, allowing administrators to define and enforce rules that determine who can access specific resources and under what conditions. The framework also includes data privacy controls to protect sensitive information, ensuring compliance with regulations and organizational policies. Additionally, it supports multi-level authentication, enabling different levels of security based on user roles, device types, or other contextual factors. The framework integrates these functionalities to provide a unified solution for securing digital interactions while maintaining usability and compliance. This approach reduces the complexity of managing multiple security systems and enhances overall system security by centralizing identity and access management. The framework is designed to be scalable, adaptable to various environments, and capable of integrating with existing security infrastructure.
Unknown
May 5, 2020
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